| Literature DB >> 17894356 |
Rhiju Das1, Bin Qian, Srivatsan Raman, Robert Vernon, James Thompson, Philip Bradley, Sagar Khare, Michael D Tyka, Divya Bhat, Dylan Chivian, David E Kim, William H Sheffler, Lars Malmström, Andrew M Wollacott, Chu Wang, Ingemar Andre, David Baker.
Abstract
We describe predictions made using the Rosetta structure prediction methodology for both template-based modeling and free modeling categories in the Seventh Critical Assessment of Techniques for Protein Structure Prediction. For the first time, aggressive sampling and all-atom refinement could be carried out for the majority of targets, an advance enabled by the Rosetta@home distributed computing network. Template-based modeling predictions using an iterative refinement algorithm improved over the best existing templates for the majority of proteins with less than 200 residues. Free modeling methods gave near-atomic accuracy predictions for several targets under 100 residues from all secondary structure classes. These results indicate that refinement with an all-atom energy function, although computationally expensive, is a powerful method for obtaining accurate structure predictions. (c) 2007 Wiley-Liss, Inc.Entities:
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Year: 2007 PMID: 17894356 DOI: 10.1002/prot.21636
Source DB: PubMed Journal: Proteins ISSN: 0887-3585